code: def inception1(conf):
      return {
          "layer": Inception,
          "partitions": (
              (
                  {
                      "layer": ConvLayer,
                      "common": conv1,
                      "relu": True,
                      "K": conf[0][0],
                  },
              ),
              (
                  {
                      "layer": ConvLayer,
                      "common": conv1,
                      "relu": True,
                      "K": conf[1][0],
                  },
                  {
                      "layer": ConvLayer,
                      "common": conv3,
                      "relu": True,
                      "K": conf[1][1],
                  },
              ),
              (
                  {
                      "layer": ConvLayer,
                      "common": conv1,
                      "relu": True,
                      "K": conf[2][0],
                  },
                  {
                      "layer": ConvLayer,
                      "common": conv5,
                      "relu": True,
                      "K": conf[2][1],
                  },
              ),
              (
                  {
                      "layer": PoolLayer,
                      "common": pool3s1p1,
                      "op": "max",
                  },
                  {
                      "layer": ConvLayer,
                      "common": conv1,
                      "relu": True,
                      "K": conf[3][0],
                  },
              ),
          ),
      }
  
file_path: neon/neon/backends/convnet-benchmarks.py
imports: from __future__ import division
  import numpy
  import pycuda.driver
  from neon import logger
  from neon.backends.nervanagpu import NervanaGPU
  from neon.backends.layer_gpu import Layer, DataLayer, ConvLayer, PoolLayer, FullLayer, Inception, BatchNorm
label_desc: Use image node_id 1 for calling a global function with example usage: inception1(conf) and returns: dict